Outliers: Detection and Analysis

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Series: Mathematics Research Developments
BISAC: MAT000000; MAT029050
DOI: https://doi.org/10.52305/HNKB4808

This brief monograph, in the broadest terms, reviews some of the techniques for outlier detection and analysis. In addition, the effect of the presence of outliers on the statistical parameters such as higher-order moments, quartiles, deciles, percentiles, skewness, and kurtosis, etc. of the distribution are studied. It also discusses the masking and swamping effect of outliers and some primitive methods of detecting these behaviors. Furthermore, some methods of detecting outliers in multivariate data using the clustering algorithm approach are also discussed.

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Table of Contents

Preface

About the Authors

Chapter 1. Introduction

Chapter 2. Outliers: To Discard or Not to Discard

Chapter 3. Methods of Outlier Detection

Chapter 4. Challenges and Impacts of Outlier Detection

Chapter 5. Statistical Tests for Outlier Detection and Outlier Treatment

Chapter 6. Other Statistical Methods

Chapter 7. Outliers in the Real World

Chapter 8. Outlier Detection in Time Series Data

Chapter 9. Discussion and Conclusion

References

Index

Additional information

Binding

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